Introduction to Statistics with JASP

From basic to advanced procedures

JASP is a free multi-platform open-source statistics package, developed and continually updated by a group of researchers at the University of Amsterdam. It has a simple drag and drop interface, easy access menus, intuitive analysis with real-time computation, and a display of all results. JASP can perform from basic data analysis (descriptive statistics such as central tendency, dispersion, histograms, scatter plots, box-plots, raincloud plots, comparisons between groups and between measures such as t-test, Analysis of Variance, non-parametric tests such as Mann-Whitney, Wilcoxon, Kruskal-Wallis, Friedman, parametric and non-parametric correlations, simple and multiple regressions, linear mixed models, generalized linear mixed models) to more advanced data analysis such as factorial analysis, networks analysis, meta-analysis, structural equation modeling, visual modeling, machine learning and many more.

What you’ll learn

  • To handle databases and results in JASP.
  • To perform data analysis with JASP, from basic to advanced.
  • To construct an validate complex predictive models with JASP.
  • To find patterns in the data with JASP.

Course Content

  • Downloading JASP and importing databases –> 3 lectures • 11min.
  • 2. Handling data & transforming variables with JASP –> 4 lectures • 50min.
  • 3. Descriptive statistics. Proportions comparison. Pearson correlation –> 3 lectures • 31min.
  • 4. Comparisons between groups with JASP –> 4 lectures • 44min.
  • 5. Simple and multiple linear regression with JASP –> 3 lectures • 22min.
  • 6. Logistic regression. Factorial ANOVA and ANCOVA –> 4 lectures • 30min.

Introduction to Statistics with JASP

Requirements

  • Basic knowledge of arithmetic and algebra.
  • Basic knowledge of statistics is an advantage.

JASP is a free multi-platform open-source statistics package, developed and continually updated by a group of researchers at the University of Amsterdam. It has a simple drag and drop interface, easy access menus, intuitive analysis with real-time computation, and a display of all results. JASP can perform from basic data analysis (descriptive statistics such as central tendency, dispersion, histograms, scatter plots, box-plots, raincloud plots, comparisons between groups and between measures such as t-test, Analysis of Variance, non-parametric tests such as Mann-Whitney, Wilcoxon, Kruskal-Wallis, Friedman, parametric and non-parametric correlations, simple and multiple regressions, linear mixed models, generalized linear mixed models) to more advanced data analysis such as factorial analysis, networks analysis, meta-analysis, structural equation modeling, visual modeling, machine learning and many more.

I think that everybody who is interested in data analysis deserves to know about JASP and to learn how to use it.

I invite you to join me on this learning journey. At this moment, there are several analytical modules from JASP for which I have already generated learning tutorials, but this is an ongoing process, and this course is growing from one week to another.

I need a companion on this journey. So what are you waiting for? Let’s go!

Get Tutorial